Macrosomia, Perinatal and Infant Mortality in Cree Communities in Quebec, 1996-2010
Bibliographic record
Abstract
BACKGROUND: Cree births in Quebec are characterized by the highest reported prevalence of macrosomia (~35%) in the world. It is unclear whether Cree births are at greater elevated risk of perinatal and infant mortality than other First Nations relative to non-Aboriginal births in Quebec, and if macrosomia may be related. METHODS: This was a population-based retrospective birth cohort study using the linked birth-infant death database for singleton births to mothers from Cree (n = 5,340), other First Nations (n = 10,810) and non-Aboriginal (n = 229,960) communities in Quebec, 1996-2010. Community type was ascertained by residential postal code and municipality name. The primary outcomes were perinatal and infant mortality. RESULTS: Macrosomia (birth weight for gestational age >90th percentile) was substantially more frequent in Cree (38.0%) and other First Nations (21.9%) vs non-Aboriginal (9.4%) communities. Comparing Cree and other First Nations vs non-Aboriginal communities, perinatal mortality rates were 1.52 (95% confidence intervals 1.17, 1.98) and 1.34 (1.10, 1.64) times higher, and infant mortality rates 2.27 (1.71, 3.02) and 1.49 (1.16, 1.91) times higher, respectively. The risk elevations in perinatal and infant death in Cree communities attenuated after adjusting for maternal characteristics (age, education, marital status, parity), but became greater after further adjustment for birth weight (small, appropriate, or large for gestational age). CONCLUSIONS: Cree communities had greater risk elevations in perinatal and infant mortality than other First Nations relative to non-Aboriginal communities in Quebec. High prevalence of macrosomia did not explain the elevated risk of perinatal and infant mortality in Cree communities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".